# Introduction:
Department

Here are preliminary results of the bibliometric mapping of the 2022 Luxembourg research evaluation. Its purpose is:

The method for the research-field-mapping can be reiviewed here:

Rakas, M., & Hain, D. S. (2019). The state of innovation system research: What happens beneath the surface?. Research Policy, 48(9), 103787.

Seed Articles

The seed articles deemed representative for the active areas of research in the institution, and include authors affiliated with the institution. They can be selected in three ways:

  1. Via bibliographic clustering of the institutions publications and selection of most central articles per cluster (only clsuters where n >= 0.05N). Selection can be found at: https://github.com/daniel-hain/biblio_lux_2022/blob/master/output/seed/scopus_liser_lm_seed.csv
  2. Manual selection of relevant publications.
  3. A combination of 1. and 2.

The present analysis is based on the following seed articles:

AU PY TI JI
THOMAS A 2021 ‘HEART OF STEEL’: HOW TRADE UNIONS LOBBY THE EUROPEAN UNION OVER EMISSIONS TRADING ENVIRON. POLIT.
MARTIN L 2020 HOW TO RETAIN MOTIVATED EMPLOYEES IN THEIR JOBS? ECON. IND. DEMOCR.
ALBANESE A;COCKX B;THUY Y 2020 WORKING TIME REDUCTIONS AT THE END OF THE CAREER: DO THEY PROLONG THE TIME SPENT IN EMPLOYMENT? EMPIR. ECON.
CATANZARO D;PESENTI R;WOLSEY L 2020 ON THE BALANCED MINIMUM EVOLUTION POLYTOPE DISCRETE OPTIM.
BURZYNSKI M;DEUSTER C;DOCQU… 2020 GEOGRAPHY OF SKILLS AND GLOBAL INEQUALITY J. DEV. ECON.
WALTHER OJ;TENIKUE M;TRÉMOL… 2019 ECONOMIC PERFORMANCE, GENDER AND SOCIAL NETWORKS IN WEST AFRICAN FOOD SYSTEMS WORLD DEV.
POUSSING N 2019 DOES CORPORATE SOCIAL RESPONSIBILITY ENCOURAGE SUSTAINABLE INNOVATION ADOPTION? EMPIRICAL EVIDENC… CORP. SOC. RESPONSIB. ENVIR…
COSAERT S 2019 WHAT TYPES ARE THERE? COMPUT. ECON.
MOTHE C;NGUYEN-THI UT 2017 PERSISTENT OPENNESS AND ENVIRONMENTAL INNOVATION: AN EMPIRICAL ANALYSIS OF FRENCH MANUFACTURING F… J. CLEAN. PROD.
NAGORE GARCÍA A;VAN SOEST A 2017 NEW JOB MATCHES AND THEIR STABILITY BEFORE AND DURING THE CRISIS INT. J. MANPOW.

Topic modelling

Here, we report the results of a LDA topic-modelling (basically, clustering on words) on all title+abstract texts.

Topics by topwords

Note: While this static vies is helpful, I recommend using the interactive LDAVis version to be found under https://daniel-hain.github.io/biblio_lux_2022/output/topic_modelling/LDAviz_liser_lm.rds/index.html#topic=1&lambda=0.60&term=. For functionality and usage, see technical description in the next tab.

Topics over time

Technical Description

LDA Topic Modelling

Topic modeling is a type of statistical modeling for discovering the abstract “topics” that occur in a collection of documents. Latent Dirichlet Allocation (LDA) is an example of topic model and is used to classify text in a document to a particular topic.

LDA is a generative probabilistic model that assumes each topic is a mixture over an underlying set of words, and each document is a mixture of over a set of topic probabilities. It builds a topic per document model and words per topic model, modeled as Dirichlet distributions.

LDAVis

LDAvis is a web-based interactive visualisation of topics estimated using LDA. It provides a global view of the topics (and how they differ from each other), while at the same time allowing for a deep inspection of the terms most highly associated with each individual topic. The package extracts information from a fitted LDA topic model to inform an interactive web-based visualization. The visualisation has two basic pieces.

The left panel visualise the topics as circles in the two-dimensional plane whose centres are determined by computing the Jensen–Shannon divergence between topics, and then by using multidimensional scaling to project the inter-topic distances onto two dimensions. Each topic’s overall prevalence is encoded using the areas of the circles.

The right panel depicts a horizontal bar chart whose bars represent the individual terms that are the most useful for interpreting the currently selected topic on the left. A pair of overlaid bars represent both the corpus-wide frequency of a given term as well as the topic-specific frequency of the term.

The \(\lambda\) slider allows to rank the terms according to term relevance. By default, the terms of a topic are ranked in decreasing order according their topic-specific probability ( \(\lambda\) = 1 ). Moving the slider allows to adjust the rank of terms based on much discriminatory (or “relevant”) are for the specific topic. The suggested optimal value of \(\lambda\) is 0.6.

Knowledge Bases: Co-Citation network analysis

Note: This analysis refers the co-citation analysis, where the cited references and not the original publications are the unit of analysis. See tab Technical descriptionfor additional explanations

Knowledge Bases summary

In order to partition networks into components or clusters, we deploy a community detection technique based on the Lovain Algorithm (Blondel et al., 2008). The Lovain Algorithm is a heuristic method that attempts to optimize the modularity of communities within a network by maximizing within- and minimizing between-community connectivity. We identify the following communities = knowledge bases.

com name dgr_int dgr
Knowledge Base 1: KB 1 (n = 3260, density =3.42)
1 COHEN W.M. LEVINTHAL D.A. ABSORPTIVE CAPACITY: A NEW PERSPECTIVE ON LEARNING AND INNOVATION (1990) 16181 19103
1 LAURSEN K. SALTER A. OPEN FOR INNOVATION: THE ROLE OF OPENNESS IN EXPLAINING INNOVATION PERFORMANCE AMONG UK MANUFACTURING FIRMS (2006) 9613 10417
1 ZAHRA S.A. GEORGE G. ABSORPTIVE CAPACITY: A REVIEW RECONCEPTUALIZATION AND EXTENSION (2002) 7580 8657
1 KATILA R. AHUJA G. SOMETHING OLD SOMETHING NEW: A LONGITUDINAL STUDY OF SEARCH BEHAVIOR AND NEW PRODUCT INTRODUCTION (2002) 6587 7080
1 DAHLANDER L. GANN D.M. HOW OPEN IS INNOVATION? (2010) 5968 6436
1 LAURSEN K. SALTER A. OPEN FOR INNOVATION: THE ROLE OF OPENNESS IN EXPLAINING INNOVATION PERFORMANCE AMONG U.K. MANUFACTURING FIRMS (2006) 4806 5260
1 CASSIMAN B. VEUGELERS R. IN SEARCH OF COMPLEMENTARITY IN INNOVATION STRATEGY: INTERNAL R&D AND EXTERNAL KNOWLEDGE ACQUISITION (2006) 4763 5270
1 LEIPONEN A. HELFAT C.E. INNOVATION OBJECTIVES KNOWLEDGE SOURCES AND THE BENEFITS OF BREADTH (2010) 4602 4929
1 MARCH J.G. EXPLORATION AND EXPLOITATION IN ORGANIZATIONAL LEARNING (1991) 4438 5013
1 GRANT R.M. TOWARD A KNOWLEDGE-BASED THEORY OF THE FIRM (1996) 4368 5039
Knowledge Base 2: KB 2 (n = 2856, density =3.22)
2 HUSELID M.A. THE IMPACT OF HUMAN RESOURCE MANAGEMENT PRACTICES ON TURNOVER PRODUCTIVITY AND CORPORATE FINANCIAL PERFORMANCE (1995) 7484 7863
2 BLAU P.M. (1964) 5504 5896
2 JIANG K. LEPAK D.P. HU J. BAER J.C. HOW DOES HUMAN RESOURCE MANAGEMENT INFLUENCE ORGANIZATIONAL OUTCOMES? A META-ANALYTIC INVESTIGATION OF MEDIATIN… 3370 3525
2 GAGNÉ M. DECI E.L. SELF-DETERMINATION THEORY AND WORK MOTIVATION (2005) 3331 3362
2 COMBS J. LIU Y. HALL A. KETCHEN D. HOW MUCH DO HIGH-PERFORMANCE WORK PRACTICES MATTER? A META-ANALYSIS OF THEIR EFFECTS ON ORGANIZATIONAL PERFORMAN… 3317 3421
2 MACDUFFIE J.P. HUMAN RESOURCE BUNDLES AND MANUFACTURING PERFORMANCE: ORGANIZATIONAL LOGIC AND FLEXIBLE PRODUCTION SYSTEMS IN THE WORLD AUTO INDUSTR… 2822 2934
2 ARTHUR J.B. EFFECTS OF HUMAN RESOURCE SYSTEMS ON MANUFACTURING PERFORMANCE AND TURNOVER (1994) 2689 2774
2 TAKEUCHI R. LEPAK D.P. WANG H. TAKEUCHI K. AN EMPIRICAL EXAMINATION OF THE MECHANISMS MEDIATING BETWEEN HIGH-PERFORMANCE WORK SYSTEMS AND THE PERFO… 2592 2637
2 LIAO H. TOYA K. LEPAK D.P. HONG Y. DO THEY SEE EYE TO EYE? MANAGEMENT AND EMPLOYEE PERSPECTIVES OF HIGH-PERFORMANCE WORK SYSTEMS AND INFLUENCE PROC… 2590 2635
2 BOSELIE P. DIETZ G. BOON C. COMMONALITIES AND CONTRADICTIONS IN HRM AND PERFORMANCE RESEARCH (2005) 2556 2618
Knowledge Base 3: KB 3 (n = 1859, density =2.18)
3 SOLOW R.M. A CONTRIBUTION TO THE THEORY OF ECONOMIC GROWTH (1956) 1491 1536
3 LUCAS R.E. ON THE MECHANICS OF ECONOMIC DEVELOPMENT (1988) 1427 1457
3 ROMER P.M. ENDOGENOUS TECHNOLOGICAL CHANGE (1990) 1107 1248
3 MANKIW N.G. ROMER D. WEIL D.N. A CONTRIBUTION TO THE EMPIRICS OF ECONOMIC GROWTH (1992) 933 954
3 AUTOR D.H. LEVY F. MURNANE R.J. THE SKILL CONTENT OF RECENT TECHNOLOGICAL CHANGE: AN EMPIRICAL EXPLORATION (2003) 844 850
3 HALL R.E. JONES C.I. WHY DO SOME COUNTRIES PRODUCE SO MUCH MORE OUTPUT PER WORKER THAN OTHERS? (1999) 837 837
3 ROMER P.M. INCREASING RETURNS AND LONG-RUN GROWTH (1986) 767 861
3 BARRO R.J. ECONOMIC GROWTH IN A CROSS SECTION OF COUNTRIES (1991) 760 769
3 GROGGER J. HANSON G.H. INCOME MAXIMIZATION AND THE SELECTION AND SORTING OF INTERNATIONAL MIGRANTS (2011) 747 750
3 BLUNDELL R. BOND S. INITIAL CONDITIONS AND MOMENT RESTRICTIONS IN DYNAMIC PANEL DATA MODELS (1998) 746 877
Knowledge Base 4: KB 4 (n = 1749, density =5.4)
4 MCWILLIAMS A. SIEGEL D. CORPORATE SOCIAL RESPONSIBILITY: A THEORY OF THE FIRM PERSPECTIVE (2001) 7475 8090
4 ORLITZKY M. SCHMIDT F.L. RYNES S.L. CORPORATE SOCIAL AND FINANCIAL PERFORMANCE: A META-ANALYSIS (2003) 4592 5114
4 SURROCA J. TRIBÓ J.A. WADDOCK S. CORPORATE RESPONSIBILITY AND FINANCIAL PERFORMANCE: THE ROLE OF INTANGIBLE RESOURCES (2010) 3090 3389
4 FREEMAN R.E. (1984) 3046 3364
4 MCWILLIAMS A. SIEGEL D.S. WRIGHT P.M. CORPORATE SOCIAL RESPONSIBILITY: STRATEGIC IMPLICATIONS (2006) 2875 3039
4 MARGOLIS J.D. WALSH J.P. MISERY LOVES COMPANIES: RETHINKING SOCIAL INITIATIVES BY BUSINESS (2003) 2635 2746
4 CARROLL A.B. A THREE-DIMENSIONAL CONCEPTUAL MODEL OF CORPORATE PERFORMANCE (1979) 2194 2364
4 MCWILLIAMS A. SIEGEL D. CORPORATE SOCIAL RESPONSIBILITY AND FINANCIAL PERFORMANCE: CORRELATION OR MISSPECIFICATION? (2000) 2116 2256
4 CAMPBELL J.L. WHY WOULD CORPORATIONS BEHAVE IN SOCIALLY RESPONSIBLE WAYS? AN INSTITUTIONAL THEORY OF CORPORATE SOCIAL RESPONSIBILITY (2007) 2067 2288
4 WADDOCK S.A. GRAVES S.B. THE CORPORATE SOCIAL PERFORMANCE-FINANCIAL PERFORMANCE LINK (1997) 1964 2049
Knowledge Base 5: KB 5 (n = 1568, density =6.53)
5 DE MARCHI V. ENVIRONMENTAL INNOVATION AND R&D COOPERATION: EMPIRICAL EVIDENCE FROM SPANISH MANUFACTURING FIRMS (2012) 5510 7307
5 KESIDOU E. DEMIREL P. ON THE DRIVERS OF ECO-INNOVATIONS: EMPIRICAL EVIDENCE FROM THE UK (2012) 3439 3932
5 TRIGUERO A. MORENO-MONDÉJAR L. DAVIA M.A. DRIVERS OF DIFFERENT TYPES OF ECO-INNOVATION IN EUROPEAN SMES (2013) 3018 3512
5 HORBACH J. DETERMINANTS OF ENVIRONMENTAL INNOVATION—NEW EVIDENCE FROM GERMAN PANEL DATA SOURCES (2008) 2463 2929
5 PORTER M.E. VAN DER LINDE C. TOWARD A NEW CONCEPTION OF THE ENVIRONMENT-COMPETITIVENESS RELATIONSHIP (1995) 2413 3061
5 CARRILLO-HERMOSILLA J. DEL RÍO P. KÖNNÖLÄ T. DIVERSITY OF ECO-INNOVATIONS: REFLECTIONS FROM SELECTED CASE STUDIES (2010) 2262 2645
5 DEMIREL P. KESIDOU E. STIMULATING DIFFERENT TYPES OF ECO-INNOVATION IN THE UK: GOVERNMENT POLICIES AND FIRM MOTIVATIONS (2011) 2015 2253
5 CAINELLI G. DE MARCHI V. GRANDINETTI R. DOES THE DEVELOPMENT OF ENVIRONMENTAL INNOVATION REQUIRE DIFFERENT RESOURCES? EVIDENCE FROM SPANISH MANUFAC… 1901 2344
5 WAGNER M. ON THE RELATIONSHIP BETWEEN ENVIRONMENTAL MANAGEMENT ENVIRONMENTAL INNOVATION AND PATENTING: EVIDENCE FROM GERMAN MANUFACTURING FIRMS (2007) 1848 2096
5 GHISETTI C. MARZUCCHI A. MONTRESOR S. THE OPEN ECO-INNOVATION MODE. AN EMPIRICAL INVESTIGATION OF ELEVEN EUROPEAN COUNTRIES (2015) 1808 2422
Knowledge Base 6: KB 6 (n = 1087, density =5.4)
6 BURT R.S. (1992) 3382 3959
6 MCPHERSON M. SMITH-LOVIN L. COOK J.M. BIRDS OF A FEATHER: HOMOPHILY IN SOCIAL NETWORKS (2001) 2385 2482
6 COLEMAN J.S. SOCIAL CAPITAL IN THE CREATION OF HUMAN CAPITAL (1988) 2297 2625
6 BURT R.S. (2005) 1813 1973
6 GRANOVETTER M.S. THE STRENGTH OF WEAK TIES (1973) 1762 2070
6 LIN N. (2001) 1660 1730
6 WASSERMAN S. FAUST K. (1994) 1379 1656
6 GRANOVETTER M. THE STRENGTH OF WEAK TIES (1973) 1297 1445
6 BOURDIEU P. THE FORMS OF CAPITAL (1986) 1074 1127
6 BURT R.S. STRUCTURAL HOLES AND GOOD IDEAS (2004) 1045 1183

Development of Knowledge Bases

Technical description

In a co-cittion network, the strength of the relationship between a reference pair \(m\) and \(n\) (\(s_{m,n}^{coc}\)) is expressed by the number of publications \(C\) which are jointly citing reference \(m\) and \(n\).

\[s_{m,n}^{coc} = \sum_i c_{i,m} c_{i,n}\]

The intuition here is that references which are frequently cited together are likely to share commonalities in theory, topic, methodology, or context. It can be interpreted as a measure of similarity as evaluated by other researchers that decide to jointly cite both references. Because the publication process is time-consuming, co-citation is a backward-looking measure, which is appropriate to map the relationship between core literature of a field.

Research Areas: Bibliographic coupling analysis

Research Areas main summary

This is arguably the more interesting part. Here, we identify the literature’s current knowledge frontier by carrying out a bibliographic coupling analysis of the publications in our corpus. This measure uses bibliographical information of publications to establish a similarity relationship between them. Again, method details to be found in the tab Technical description. As you will see, we identify the main research area, but also a set of adjacent research areas with some theoretical/methodological/application overlap.

To identify communities in the field’s knowledge frontier (labeled research areas) we again use the Lovain Algorithm (Blondel et al., 2008). We identify the following communities = research areas.

com_name AU PY TI dgr_int TC TC_year
Research Area 1: RA 1 (n = 1181, density =0.12)
RA 1 ACEMOGLU D;RESTREPO P 2018 THE RACE BETWEEN MAN AND MACHINE: IMPLICATIONS OF TECHNOLOGY FOR GROWTH, FACTOR SHARES, AND EMPLOYMENT 4.22 313 78.25
RA 1 BHATTACHARYA M;AWAWORY… 2017 THE DYNAMIC IMPACT OF RENEWABLE ENERGY AND INSTITUTIONS ON ECONOMIC OUTPUT AND CO2 EMISSIONS ACROSS REGIONS 2.18 272 54.40
RA 1 DIAMOND R 2016 THE DETERMINANTS AND WELFARE IMPLICATIONS OF US WORKERS’ DIVERGING LOCATION CHOICES BY SKILL: 1980-2000 2.42 231 38.50
RA 1 JONES CI 2016 THE FACTS OF ECONOMIC GROWTH 5.11 100 16.67
RA 1 TEIXEIRA AAC;QUEIRÓS ASS 2016 ECONOMIC GROWTH, HUMAN CAPITAL AND STRUCTURAL CHANGE: A DYNAMIC PANEL DATA ANALYSIS 3.16 160 26.67
RA 1 DIEBOLT C;HIPPE R 2019 THE LONG-RUN IMPACT OF HUMAN CAPITAL ON INNOVATION AND ECONOMIC DEVELOPMENT IN THE REGIONS OF EUROPE 6.28 67 22.33
RA 1 BEAUDRY P;GREEN DA;SAN… 2016 THE GREAT REVERSAL IN THE DEMAND FOR SKILL AND COGNITIVE TASKS 3.52 118 19.67
RA 1 BEINE M;BERTOLI S;FERN… 2016 A PRACTITIONERS’ GUIDE TO GRAVITY MODELS OF INTERNATIONAL MIGRATION 2.84 135 22.50
RA 1 BOVE V;ELIA L 2017 MIGRATION, DIVERSITY, AND ECONOMIC GROWTH 3.80 93 18.60
RA 1 BERG A;OSTRY JD;TSANGA… 2018 REDISTRIBUTION, INEQUALITY, AND GROWTH: NEW EVIDENCE 4.59 73 18.25
Research Area 2: RA 2 (n = 1034, density =0.36)
RA 2 DECI EL;OLAFSEN AH;RYA… 2017 SELF-DETERMINATION THEORY IN WORK ORGANIZATIONS: THE STATE OF A SCIENCE 5.28 609 121.80
RA 2 SHIN D;KONRAD AM 2017 CAUSALITY BETWEEN HIGH-PERFORMANCE WORK SYSTEMS AND ORGANIZATIONAL PERFORMANCE 9.63 158 31.60
RA 2 OSTROFF C;BOWEN DE 2016 2014 DECADE AWARD INVITED ARTICLE REFLECTIONS ON THE 2014 DECADE AWARD: IS THERE STRENGTH IN THE CONSTRUCT OF HR SYSTEM ST… 6.02 211 35.17
RA 2 DELERY JE;ROUMPI D 2017 STRATEGIC HUMAN RESOURCE MANAGEMENT, HUMAN CAPITAL AND COMPETITIVE ADVANTAGE: IS THE FIELD GOING IN CIRCLES? 6.84 184 36.80
RA 2 GUEST DE 2017 HUMAN RESOURCE MANAGEMENT AND EMPLOYEE WELL-BEING: TOWARDS A NEW ANALYTIC FRAMEWORK 2.94 382 76.40
RA 2 JIANG K;MESSERSMITH J 2018 ON THE SHOULDERS OF GIANTS: A META-REVIEW OF STRATEGIC HUMAN RESOURCE MANAGEMENT 13.30 80 20.00
RA 2 WALLACE JC;BUTTS MM;JO… 2016 A MULTILEVEL MODEL OF EMPLOYEE INNOVATION: UNDERSTANDING THE EFFECTS OF REGULATORY FOCUS, THRIVING, AND EMPLOYEE INVOLVEME… 5.90 179 29.83
RA 2 CHOWHAN J 2016 UNPACKING THE BLACK BOX: UNDERSTANDING THE RELATIONSHIP BETWEEN STRATEGY, HRM PRACTICES, INNOVATION AND ORGANIZATIONAL PER… 10.87 93 15.50
RA 2 BOON C;DEN HARTOG DN;L… 2019 A SYSTEMATIC REVIEW OF HUMAN RESOURCE MANAGEMENT SYSTEMS AND THEIR MEASUREMENT 7.99 119 39.67
RA 2 SARIDAKIS G;LAI Y;COOP… 2017 EXPLORING THE RELATIONSHIP BETWEEN HRM AND FIRM PERFORMANCE: A META-ANALYSIS OF LONGITUDINAL STUDIES 6.44 122 24.40
Research Area 3: RA 3 (n = 973, density =0.68)
RA 3 FORÉS B;CAMISÓN C 2016 DOES INCREMENTAL AND RADICAL INNOVATION PERFORMANCE DEPEND ON DIFFERENT TYPES OF KNOWLEDGE ACCUMULATION CAPABILITIES AND O… 13.08 245 40.83
RA 3 WEST J;BOGERS M 2017 OPEN INNOVATION: CURRENT STATUS AND RESEARCH OPPORTUNITIES 15.12 181 36.20
RA 3 SCUOTTO V;DEL GIUDICE … 2017 KNOWLEDGE-DRIVEN PREFERENCES IN INFORMAL INBOUND OPEN INNOVATION MODES. AN EXPLORATIVE VIEW ON SMALL TO MEDIUM ENTERPRISES 13.01 206 41.20
RA 3 SANTORO G;VRONTIS D;TH… 2018 THE INTERNET OF THINGS: BUILDING A KNOWLEDGE MANAGEMENT SYSTEM FOR OPEN INNOVATION AND KNOWLEDGE MANAGEMENT CAPACITY 8.45 275 68.75
RA 3 BOGERS M;FOSS NJ;LYNGS… 2018 THE “HUMAN SIDE” OF OPEN INNOVATION: THE ROLE OF EMPLOYEE DIVERSITY IN FIRM-LEVEL OPENNESS 14.18 154 38.50
RA 3 HAANS RFJ;PIETERS C;HE… 2016 THINKING ABOUT U: THEORIZING AND TESTING U- AND INVERTED U-SHAPED RELATIONSHIPS IN STRATEGY RESEARCH 2.78 678 113.00
RA 3 FLOR ML;COOPER SY;OLTR… 2018 EXTERNAL KNOWLEDGE SEARCH, ABSORPTIVE CAPACITY AND RADICAL INNOVATION IN HIGH-TECHNOLOGY FIRMS 13.37 139 34.75
RA 3 APRILIYANTI ID;ALON I 2017 BIBLIOMETRIC ANALYSIS OF ABSORPTIVE CAPACITY 12.71 135 27.00
RA 3 SANTORO G;BRESCIANI S;… 2020 COLLABORATIVE MODES WITH CULTURAL AND CREATIVE INDUSTRIES AND INNOVATION PERFORMANCE: THE MODERATING ROLE OF HETEROGENEOUS… 14.10 121 60.50
RA 3 KOBARG S;STUMPF-WOLLER… 2019 MORE IS NOT ALWAYS BETTER: EFFECTS OF COLLABORATION BREADTH AND DEPTH ON RADICAL AND INCREMENTAL INNOVATION PERFORMANCE AT… 18.13 91 30.33
Research Area 4: RA 4 (n = 636, density =0.41)
RA 4 BLOCK P;HOFFMAN M;RAAB… 2020 SOCIAL NETWORK-BASED DISTANCING STRATEGIES TO FLATTEN THE COVID-19 CURVE IN A POST-LOCKDOWN WORLD 5.78 214 107.00
RA 4 BURT RS;BURZYNSKA K 2017 CHINESE ENTREPRENEURS, SOCIAL NETWORKS, AND GUANXI 6.83 107 21.40
RA 4 GONZÁLEZ-BAILÓN S;WANG N 2016 NETWORKED DISCONTENT: THE ANATOMY OF PROTEST CAMPAIGNS IN SOCIAL MEDIA 5.13 94 15.67
RA 4 PHUA J;JIN SV;KIM JJ 2017 USES AND GRATIFICATIONS OF SOCIAL NETWORKING SITES FOR BRIDGING AND BONDING SOCIAL CAPITAL: A COMPARISON OF FACEBOOK, TWIT… 1.71 257 51.40
RA 4 HIMELBOIM I;SMITH MA;R… 2017 CLASSIFYING TWITTER TOPIC-NETWORKS USING SOCIAL NETWORK ANALYSIS 4.21 101 20.20
RA 4 BARNES ML;LYNHAM J;KAL… 2016 SOCIAL NETWORKS AND ENVIRONMENTAL OUTCOMES 3.00 119 19.83
RA 4 BARNES M;KALBERG K;PAN… 2016 WHEN IS BROKERAGE NEGATIVELY ASSOCIATED WITH ECONOMIC BENEFITS? ETHNIC DIVERSITY, COMPETITION, AND COMMON-POOL RESOURCES 10.30 33 5.50
RA 4 KREAGER DA;SCHAEFER DR… 2016 TOWARD A CRIMINOLOGY OF INMATE NETWORKS 6.27 47 7.83
RA 4 KIM JY;HOWARD M;COX PA… 2016 UNDERSTANDING NETWORK FORMATION IN STRATEGY RESEARCH: EXPONENTIAL RANDOM GRAPH MODELS 4.37 59 9.83
RA 4 VENKATARAMANI V;ZHOU L… 2016 SOCIAL NETWORKS AND EMPLOYEE VOICE: THE INFLUENCE OF TEAM MEMBERS’ AND TEAM LEADERS’ SOCIAL NETWORK POSITIONS ON EMPLOYEE … 3.75 66 11.00
Research Area 5: RA 5 (n = 621, density =0.53)
RA 5 WANG Q;DOU J;JIA S 2016 A META-ANALYTIC REVIEW OF CORPORATE SOCIAL RESPONSIBILITY AND CORPORATE FINANCIAL PERFORMANCE: THE MODERATING EFFECT OF CO… 11.10 274 45.67
RA 5 KANG C;GERMANN F;GREWAL R 2016 WASHING AWAY YOUR SINS? CORPORATE SOCIAL RESPONSIBILITY, CORPORATE SOCIAL IRRESPONSIBILITY, AND FIRM PERFORMANCE 7.10 218 36.33
RA 5 EL GHOUL S;GUEDHAMI O;… 2017 COUNTRY-LEVEL INSTITUTIONS, FIRM VALUE, AND THE ROLE OF CORPORATE SOCIAL RESPONSIBILITY INITIATIVES 6.97 216 43.20
RA 5 BANSAL P;SONG H-C 2017 SIMILAR BUT NOT THE SAME: DIFFERENTIATING CORPORATE SUSTAINABILITY FROM CORPORATE RESPONSIBILITY 5.72 240 48.00
RA 5 HAWN O;IOANNOU I 2016 MIND THE GAP: THE INTERPLAY BETWEEN EXTERNAL AND INTERNAL ACTIONS IN THE CASE OF CORPORATE SOCIAL RESPONSIBILITY 8.37 160 26.67
RA 5 GREWATSCH S;KLEINDIENST I 2017 WHEN DOES IT PAY TO BE GOOD? MODERATORS AND MEDIATORS IN THE CORPORATE SUSTAINABILITY–CORPORATE FINANCIAL PERFORMANCE RELA… 10.14 125 25.00
RA 5 KIM K-H;KIM M;QIAN C 2018 EFFECTS OF CORPORATE SOCIAL RESPONSIBILITY ON CORPORATE FINANCIAL PERFORMANCE: A COMPETITIVE-ACTION PERSPECTIVE 8.04 152 38.00
RA 5 MELLAHI K;FRYNAS JG;SU… 2016 A REVIEW OF THE NONMARKET STRATEGY LITERATURE: TOWARD A MULTI-THEORETICAL INTEGRATION 4.18 289 48.17
RA 5 RHOU Y;SINGAL M;KOH Y 2016 CSR AND FINANCIAL PERFORMANCE: THE ROLE OF CSR AWARENESS IN THE RESTAURANT INDUSTRY 7.25 118 19.67
RA 5 PRICE JM;SUN W 2017 DOING GOOD AND DOING BAD: THE IMPACT OF CORPORATE SOCIAL RESPONSIBILITY AND IRRESPONSIBILITY ON FIRM PERFORMANCE 7.13 118 23.60
Research Area 6: RA 6 (n = 620, density =0.54)
RA 6 HOJNIK J;RUZZIER M 2016 WHAT DRIVES ECO-INNOVATION? A REVIEW OF AN EMERGING LITERATURE 9.72 248 41.33
RA 6 BOSSLE MB;DUTRA DE BAR… 2016 THE DRIVERS FOR ADOPTION OF ECO-INNOVATION 8.85 255 42.50
RA 6 XIE X;HUO J;ZOU H 2019 GREEN PROCESS INNOVATION, GREEN PRODUCT INNOVATION, AND CORPORATE FINANCIAL PERFORMANCE: A CONTENT ANALYSIS METHOD 6.90 225 75.00
RA 6 DORAN J;RYAN G 2016 THE IMPORTANCE OF THE DIVERSE DRIVERS AND TYPES OF ENVIRONMENTAL INNOVATION FOR FIRM PERFORMANCE 8.46 178 29.67
RA 6 DANGELICO RM 2016 GREEN PRODUCT INNOVATION: WHERE WE ARE AND WHERE WE ARE GOING 6.26 237 39.50
RA 6 HOJNIK J;RUZZIER M 2016 THE DRIVING FORCES OF PROCESS ECO-INNOVATION AND ITS IMPACT ON PERFORMANCE: INSIGHTS FROM SLOVENIA 9.08 145 24.17
RA 6 DEL RÍO P;PEÑASCO C;RO… 2016 WHAT DRIVES ECO-INNOVATORS? A CRITICAL REVIEW OF THE EMPIRICAL LITERATURE BASED ON ECONOMETRIC METHODS 9.72 135 22.50
RA 6 BARBIERI N;GHISETTI C;… 2016 A SURVEY OF THE LITERATURE ON ENVIRONMENTAL INNOVATION BASED ON MAIN PATH ANALYSIS 11.64 107 17.83
RA 6 ZHANG Y-J;PENG Y-L;MA … 2017 CAN ENVIRONMENTAL INNOVATION FACILITATE CARBON EMISSIONS REDUCTION? EVIDENCE FROM CHINA 3.58 327 65.40
RA 6 CAI W;LI G 2018 THE DRIVERS OF ECO-INNOVATION AND ITS IMPACT ON PERFORMANCE: EVIDENCE FROM CHINA 5.26 212 53.00
Research Area 7: RA 7 (n = 557, density =0.3)
RA 7 LI F;MORGAN KL;ZASLAVS… 2018 BALANCING COVARIATES VIA PROPENSITY SCORE WEIGHTING 8.91 229 57.25
RA 7 AUSTIN PC;LEE DS;FINE JP 2016 INTRODUCTION TO THE ANALYSIS OF SURVIVAL DATA IN THE PRESENCE OF COMPETING RISKS 1.44 904 150.67
RA 7 ABADIE A;IMBENS GW 2016 MATCHING ON THE ESTIMATED PROPENSITY SCORE 3.00 282 47.00
RA 7 JOACHIMS T;SWAMINATHAN… 2017 UNBIASED LEARNING-TO-RANK WITH BIASED FEEDBACK 2.43 193 38.60
RA 7 FONG C;HAZLETTAND C;IM… 2018 COVARIATE BALANCING PROPENSITY SCORE FOR A CONTINUOUS TREATMENT: APPLICATION TO THE EFFICACY OF POLITICAL ADVERTISEMENTS 5.67 79 19.75
RA 7 ABADIE A;CATTANEO MD 2018 ECONOMETRIC METHODS FOR PROGRAM EVALUATION 4.18 105 26.25
RA 7 BELL DR;GALLINO S;MORE… 2018 OFFLINE SHOWROOMS IN OMNICHANNEL RETAIL: DEMAND AND OPERATIONAL BENEFITS 1.79 214 53.50
RA 7 CHAN KCG;YAM SCP;ZHANG Z 2016 GLOBALLY EFFICIENT NON-PARAMETRIC INFERENCE OF AVERAGE TREATMENT EFFECTS BY EMPIRICAL BALANCING CALIBRATION WEIGHTING 5.63 61 10.17
RA 7 JORDÀ O;TAYLOR AM 2016 THE TIME FOR AUSTERITY: ESTIMATING THE AVERAGE TREATMENT EFFECT OF FISCAL POLICY 2.95 107 17.83
RA 7 GORDON BR;ZETTELMEYER … 2019 A COMPARISON OF APPROACHES TO ADVERTISING MEASUREMENT: EVIDENCE FROM BIG FIELD EXPERIMENTS AT FACEBOOK 5.86 47 15.67

Development

Connectivity between the research areas

Technical description

In a bibliographic coupling network, the coupling-strength between publications is determined by the number of commonly cited references they share, assuming a common pool of references to indicate similarity in context, methods, or theory. Formally, the strength of the relationship between a publication pair \(i\) and \(j\) (\(s_{i,j}^{bib}\)) is expressed by the number of commonly cited references.

\[s_{i,j}^{bib} = \sum_m c_{i,m} c_{j,m}\]

Since our corpus contains publications which differ strongly in terms of the number of cited references, we normalize the coupling strength by the Jaccard similarity coefficient. Here, we weight the intercept of two publications’ bibliography (shared refeences) by their union (number of all references cited by either \(i\) or \(j\)). It is bounded between zero and one, where one indicates the two publications to have an identical bibliography, and zero that they do not share any cited reference. Thereby, we prevent publications from having high coupling strength due to a large bibliography (e.g., literature surveys).

\[S_{i,j}^{jac-bib} =\frac{C(i \cap j)}{C(i \cup j)} = \frac{s_{i,j}^{bib}}{c_i + c_j - s_{i,j}^{bib}}\]

More recent articles have a higher pool of possible references to co-cite to, hence they are more likely to be coupled. Consequently, bibliographic coupling represents a forward looking measure, and the method of choice to identify the current knowledge frontier at the point of analysis.

Knowledge Bases, Research Areas & Topics Interaction

Endnotes

All results are preliminary so far…